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Case Study: The Effective Use of an Extensive Logical rule Based Data Analytics Approach in Establishing Root Cause of Performance Issues in Widespread Deployments of Unitary Space Air Conditioning Units
Abstract
Today a significant percentage of office spaces are air conditioned using widely deployed
unitary systems, either Fan Coil Units (FCU) or Variable Air Volume (VAV) boxes, to
achieve high degrees of air conditioned zonal control. However establishing a near realtime
overall control monitoring regime to ensure proper control adherence across such large
estates can be difficult, or possibly unattainable, where the number of units could effectively
run into the hundreds, if not the thousands.
And, as is outlined in the problem definition section of this paper, compounding normal
operational control issues such as system tuning and hardware failures, with inbuilt design
limitations and poor building fabric issues, coupled with embedded deep rooted and
undetected commissioning problems, and all functioning within a dynamic operational
environment, one can see that the task of effective and timely root cause analysis can be an
extremely difficult one.
Having being challenged with such a problem environment, the author attempts, through
presentation of a series of actual real life working examples, to offer the reader the case for
use of an effective and efficient aggregated data driven analytical approach, which includes
temporal and geo spatial visualisation techniques, that makes the identification of the
fundamental root cause problems, and system interactions (positive and negative) within this
complex operational environment analysis, possible.
The presented approach therefore offers the SME community a means to detect the current
underlying problems without the need for deployment of costly disruptive diagnostic
procedures or preventative maintenance regimes. Such an approach also demonstrates the
flexibility to cater for future problem diagnosis scenarios where the underlying logical rules
built within the underlying architecture can be written, tested and deployed in a timely
fashion. Finally it is contended that this targeted aggregated data driven fault diagnosis
approach is equally applicable in any other situation which entails wide spread deployment of
energy assets, for example, high volume deployments of store refrigeration units used within
the Retail sector.
Citation
Brady, N. (2013). Case Study: The Effective Use of an Extensive Logical rule Based Data Analytics Approach in Establishing Root Cause of Performance Issues in Widespread Deployments of Unitary Space Air Conditioning Units. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from https : / /hdl .handle .net /1969 .1 /151453.